Workload Allocation in Hierarchical Cloudlet Networks

Qiang Fan, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

Edge cloudlets are promising to mitigate the high network delay incurred by the remote cloud in executing workloads offloaded from a user equipment (UE). However, the response time of a task request consists of both the network delay and computing delay. Considering the spatial and temporal dynamics of workloads among cloudlets, if the workload of an edge cloudlet is heavy, the computing delay in the cloudlet may be unbearable. In this letter, we design a hierarchical cloudlet network and propose a workload allocation scheme to minimize the average response time of UEs' requests by deciding which cloudlet a UE is assigned to and how much computing resource is provisioned to serve it. The performance of the proposed scheme is validated by extensive simulations.

Original languageEnglish (US)
Pages (from-to)820-823
Number of pages4
JournalIEEE Communications Letters
Volume22
Issue number4
DOIs
StatePublished - Apr 2018

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

Keywords

  • Cloudlet
  • edge computing
  • resource allocation
  • workload allocation

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